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1.
Higher education institutions are trying to provide more flexibility and individualization, which is mainly realized through the use of new technologies and implemented in online or blended learning designs. This systematic review aims to investigate the impact of replacing classroom time with an online learning environment. The meta-analysis (k = 21 effect sizes) applied strict inclusion criteria concerning research design, measurement of learning outcomes and implementation of blended learning. The estimated effect size (Hedge's g) was positive, although not significantly different from zero and the confidence interval [-0.13, 0.25], suggesting that overall differences between blended and conventional classroom learning are small, and, at best, very small negative or moderate positive effects are plausible. This means that despite a reduction in classroom time between 30 and 79 per cent, equivalent learning outcomes were found. Consequently, blended learning with reduced classroom time is not systematically more or less effective than conventional classroom learning.  相似文献   
2.
The article documents findings from a pilot study undertaken in 2012–2013 in a special needs secondary school in the England, that trialled the use of a multimedia advocacy tool, “The RIX Wiki”. The trial was part of the pathfinder programme, which aimed to reform existing Special Education Needs provision, from the system of statementing to one of developing education health care plans. The reforms became enshrined in the Children and Families Act (2014). The findings were overall positive and helped with person-centred planning processes. The discussion is framed within current and future policy directives. We argue that multimedia advocacy approaches and software tools, like the “RIX Wiki” will have a continued role to play in ensuring the needs, aspirations and choices of children and young people with learning disabilities remain central.  相似文献   
3.
开展信息化、智慧化预警工作是实现全面精准育人的重要途径,而预警应用平台无疑是预警工作的有力工具和实践载体,其设计方案应用效果的好坏直接决定着学习预警信息化愿景的达成度。文章在分析高职院校学习预警工作现状的基础上,从工作流程设计、平台框架设计和平台建设方法等3个方面提出了解决方案,并对平台的应用效果进行了实证分析,结果表明:平台的应用扩展了预警范围、提升了预警的精准度和时效性、提高了工作效率,且干预更为灵活、个性化,可为当前高职院校学习危机的实践改革提供新思路。  相似文献   
4.
在线健康社区用户个人健康信息管理行为特征研究   总被引:3,自引:1,他引:2  
[目的/意义] 旨在对在线健康社区用户的个人健康信息管理行为特征进行分析,并在此基础上,对"平台-PHIM-健康目标"这一模式中的元素之间的关系进行探讨。[方法/过程] 选择患有红斑狼疮的在线健康社区用户作为调查对象。采用聚类方法对个人健康信息管理行为的总体测度水平不同的群体进行识别;利用单因素方差分析(One-way ANOVA)对不同群组进行比较研究。[结果/结论] 将依托在线健康社区进行的个人健康信息管理行为界定为健康信息发现、健康信息互动和健康信息分享。从数据分析结果来看,首先,在线健康社区的红斑狼疮患者在个人健康信息管理行为水平上存在显著的高低差异。第二,用户所感知到的社会支持与其个人健康信息管理水平存在正相关关系。第三,个人健康信息管理与用户健康目标之间存在正相关关系。本研究为在线健康社区完善其服务方式,促进慢性病人个人健康信息管理水平提高提供合理建议。  相似文献   
5.
In social networking services (SNSs), users’ unclear understanding of the large and invisible audience increases the chances of online turbulence, which is a key source of SNS-induced stress. This growing phenomenon has gained increasing attention in academia and industry due to the undesirable consequences for users and SNS platforms. In this study, we draw from the transactional model of stress to examine how audience management strategies impact online turbulence and lead to neglected unintended audience concern and lurking. We also investigate the role of self-monitoring as a stress inhibitor. We test our model with data collected from 301 SNS users. The results show that the four types of audience management strategies have different effects on online turbulence, which significantly impacts neglected unintended audience concern especially when users have high self-monitoring skills. We believe that this work contributes, both from scientific and practical standpoints, to the understanding of the interventions and stressful responses of online turbulence in SNSs.  相似文献   
6.
体育是美国人生活中不可或缺的一部分,发达的体育文化为美国小镇体育的繁荣奠定了基础。研究以美国体育小镇为对象,运用文献资料、实地考察、逻辑分析及ArcGIS地理信息绘图等方法和技术对美国体育小镇进行了研究。结果表明:美国体育小镇的布局属非均匀化发展,存在东强西弱,南强北弱的特点且表现出"马太效应"。进而从社会学的角度分析了美国体育小镇运行的外部环境和内在动力机制,并以典型案例对体育小镇运行特点进行了剖析。建议我国体育小镇的建设应从目标引领、政策驱动、环境支持、形成正反馈循环和塑造灵魂等方面思考以推动体育小镇的建设。  相似文献   
7.
This study examined the extent to which maltreatment history and the characteristics of out-of-home care correlated with the language and social skills of maltreated children. Participants in this study were 82 maltreated children aged between 5 and 12 years of age. All children were residing with state-designated carers in out-of-home-care. The children were presented with standardised tests assessing language and social skills. Results showed that the sample performed significantly below the normative mean on both tests. Correlation analyses showed social skills, but not language skills were correlated with aspects of maltreatment history. The education level of the state-designated carer/s was correlated with the children's language skills; higher education level was associated with higher language skills. The study provides evidence that at the group level, language and social skills are poor in maltreated children. However, gains in language skills might be made via the out-of-home-care environment. Improvements in the social skills of maltreated children may require additional support.  相似文献   
8.
In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published.  相似文献   
9.
Social Networking Sites (SNSs) play an important role in our daily lives and the number of their users increases regularly. To understand how users can be satisfied in the complex digital environment of SNSs, this study examines how motivations and emotions combine with each other to explain high satisfaction. Users’ motivations comprise four attributes, entertainment, information, social-psychological, and convenience. Emotions are divided into their two main categories, that is positive and negative emotions. We draw on complexity and configuration theories, present a conceptual model along with propositions and perform a fuzzy-set qualitative comparative analysis (fsQCA). Through an empirically study with 582 SNSs users, we present eight combinations (configurations) of motivations and emotions that lead to high satisfaction, which highlight the role of high convenience, followed by entertainment and information motivations in being satisfied with SNSs. High satisfaction can be achieved both when positive and negative emotions are high and low, depending on how they combine users’ motivations. None of the factors are indispensable to explain high satisfaction on their own, instead they are insufficient but necessary parts of the causal combinations that explain high satisfaction. This study contributes in SNSs literature by extending current knowledge on how motivations and emotions combine to increase satisfaction, and by identifying specific patterns of users for whom these factors are important and influence greatly their satisfaction.  相似文献   
10.
基于深度学习的中文专利自动分类方法研究   总被引:2,自引:0,他引:2  
[目的/意义] 面向当前国内专利审查和专利情报分析工作中对于海量专利分类的客观需求,设计了7种基于深度学习的专利自动分类方法,对比各种方法的分类效果,从而助力专利分类效率和效果的提升。[方法/过程] 针对传统机器学习方法存在的缺陷,基于Word2Vec、CNN、RNN、Attention机制等深度学习技术,考虑专利文本语序特征、上下文特征以及分类关键特征,设计Word2Vec+TextCNN、Word2Vec+GRU、Word2Vec+BiGRU、Word2Vec+BiGRU+TextCNN等7种深度学习模型,以中国专利为例,选取IPC主分类号的"部"作为分类依据,对比这7种模型与3种传统分类模型在中文专利分类任务中的效果。[结果/结论] 实证研究效果显示,采用考虑语序特征、上下文特征及强化关键特征的深度学习方法进行中文专利分类具有更优的分类效果。  相似文献   
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